{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "from utils import OrnsteinUhlenbeckActionNoise\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.03406942772253951"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "noise = OrnsteinUhlenbeckActionNoise(action_dim=1)\n",
    "noise.sample()[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.008887709219409783 1.315020313066408\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5,1,'Ornstein-Uhlenbeck Noise')"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Simple data to display in various forms\n",
    "x = np.linspace(0, 200, 200)\n",
    "y = [noise.sample()[0] for _ in x]\n",
    "mean = np.mean(y)\n",
    "max = np.max(y)\n",
    "print(mean,max)\n",
    "plt.close('all')\n",
    "\n",
    "f, ax = plt.subplots()\n",
    "ax.plot(x, y)\n",
    "ax.set_title('Ornstein-Uhlenbeck Noise')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.5.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
